Automatic modulation classification of communication signals is very important for both military and civilian purposes. In order to automatically recognize the conventional analogue communication signals, a new method for extracting the signal feature parameters is proposed. When the carrier has been synchronized, the received signals are transformed to zero intermediate frequency and the complex base band signal vector is then rotated anticlockwise around the origin for 90 degrees. Thus, it a-voids the disadvantages caused by the discontinued phase during the processing of the DSB signal. Following that, five feature parameters based on the first statistical moments of the received signals are proposed. The calculation of all those feature parameters is less complicated and more robust. Next, an automatic modulation recognition algorithm based on the decision-theoretic approach is developed and its realization is also presented in the form of a flowchart. Finally, computer simulation results show that all the aforementioned types of analogue communication signals can be recognized with average success rate greater than 97% at an SNR above — 7dB. It is suitable for the practical application of signal detection and fast recognition in non-cooperation communication systems.%通信信号调制方式的自动识别在军用和民用方面都十分重要.为自动识别常用模拟通信信号的调制方式,本文提出一种信号特征参数提取方法,即在实现载波同步、将接收信号变换到零中频后,将复基带信号矢量围绕原点逆时针旋转90度.本方法有效克服了DSB信号处理过程中相位不连续带来的影响.本文提出五个基于接收信号一阶统计矩的特征参数,这些参数提取过程的运算量小、鲁棒性强.以判决理论为基础提出了一种调制方式自动识别算法并给出实现流程.计算机仿真结果表明,在信噪比大于-7 dB时,识别算法平均识别率不低于97％,可望用于实际非协作通信系统中信号的检测和快速识别.
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